scholarly journals A Comparison Of Real-Time Optical Correlators For Pattern Recognition

1989 ◽  
Author(s):  
K. Terry Stalker ◽  
Perry A. Molley ◽  
Bruce D. Hansche
Keyword(s):  
Pattern Recognition ◽  
Real Time ◽  
Optical Correlators

Hilbert transform and mirror-image optical correlators

2000 ◽  
Vol 39 (14) ◽  
pp. 2300 ◽  
Author(s):  
Alastair D. McAulay
Keyword(s):  
Hilbert Transform ◽  
Mirror Image ◽  
Optical Correlators

Fully complex filter implementation in all-optical and hybrid digital/optical correlators

2001 ◽  
Author(s):  
Philip M. Birch ◽  
Rupert C. D. Young ◽  
Frederic Claret-Tournier ◽  
Triantafillos Koukoulas ◽  
Sovira Tan ◽  
...  
Keyword(s):  
Complex Filter ◽  
All Optical ◽  
Optical Correlators

FLEXIBLY PROGRAMMABLE OPTO-ELECTRONIC ANALOGIC CNN COMPUTER (POAC) IMPLEMENTATION APPLYING AN EFFICIENT, UNCONVENTIONAL OPTICAL CORRELATOR ARCHITECTURE

2003 ◽  
Vol 12 (06) ◽  
pp. 739-767 ◽  
Author(s):  
SZABOLCS TŐKÉS ◽  
LÁSZLÓ ORZÓ ◽  
AHMED AYOUB ◽  
TAMÁS ROSKA
Keyword(s):  
Sensor Array ◽  
Input Image ◽  
Computer Architectures ◽  
Single Chip ◽  
Chemically Modified ◽  
Processor Arrays ◽  
Optical Correlator ◽  
Optical Correlators ◽  
Optical Computer ◽  
Processing Steps

To overcome shortcomings of the currently available optical computer architectures a programmable opto-electronic CNN array computer (POAC) is introduced. It combines the optical correlators' supreme resolution and complexity with the versatility of the single chip adaptive visual CNN-UM sensor and processor arrays. The system is grounded on an unconventional optical correlator architecture, which is a modified joint Fourier transform correlator. This architecture uses the angular coding of the template pixels and applies the template not in the recording phase, but in the reconstruction phase of correlation. Feasibility of this concept has been successfully demonstrated by a breadboard model. It computes correlation in two consecutive steps: First a hologram of the input image is recorded in a dynamic holographic material (we used chemically-modified Bacteriorhodopsin film samples). Next, angularly-coded read-out beams reconstruct the appropriately weighted and shifted replicas of the stored input image. Superposition of these copies produces the correlogram. A programmable adaptive sensor array, a special Visual CNN-UM chip detects the resulting correlogram. So, both the sensing and the required post-processing steps are accomplished in a parallel way. The introduced opto-electronic architecture provides exceptional synergy and good compromise of the applicable technologies and the system performance.

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